Passive seismic event estimation using multi-scattering waveform inversion

Passive seismic event estimation using multi-scattering waveform inversion

Chao Song, Zedong Wu and Tariq Alkhalifah, "Passive seismic event estimation using multi-scattering waveform inversion", Geophysics 84 (2019): 1942-2156.​​ doi: 10.1190/geo2018-0358.1
BibTeX​ 
Chao Song, Zedong Wu, Tariq Alkhalifah
microseismic, passive seismic, full-waveform inversion, frequency-domain
2019
​Passive seismic monitoring has become an effective method to understand underground processes. Time-reversal-based methods are often used to locate passive seismic events directly. However, these kinds of methods are strongly dependent on the accuracy of the velocity model. Full-waveform inversion (FWI) has been used on passive seismic data to invert the velocity model and source image, simultaneously. However, waveform inversion of passive seismic data uses mainly the transmission energy, which results in poor illumination and low resolution. We developed a waveform inversion using multiscattered energy for passive seismic to extract more information from the data than conventional FWI. Using transmission wavepath information from single- and double-scattering, computed from a predicted scatterer field acting as secondary sources, our method provides better illumination of the velocity model than conventional FWI. Using a new objective function, we optimized the source image and velocity model, including multiscattered energy, simultaneously. Because we conducted our method in the frequency domain with a complex source function including spatial and wavelet information, we mitigate the uncertainties of the source wavelet and source origin time. Inversion results from the Marmousi model indicate that by taking advantage of multiscattered energy and starting from a reasonably acceptable frequency (a single source at 3 Hz and multiple sources at 5 Hz), our method yields better inverted velocity models and source images compared with conventional FWI.
(print): 0016-8033 (online): 1942-2156